Differences in circadian variation in QT interval of the ECG in women compared to men.
Bibliographic record
Abstract
BACKGROUND: Measurement of the QT interval in the ECG (QT interval) is important in evaluating risk for cardiac death and for assessing the impact of drugs on the heart. The objective of this study is to determine whether the time of day affects the QT interval, QT interval variability and whether these relationships are influenced by an individual's sex. METHODS: Twenty-four hour ECGs were analyzed in detail on 50 individuals, 49 years of age, without evidence of coronary artery disease, structural heart disease, or significant arrhythmias. Four different QT-heart rate adjustment formulae were calculated and compared. RESULTS: There were significant (P=0.0014) differences between the QT-heart rate relationship during three different time-periods (night 00:00 to 08:00 h, day 08:00 to 14:00 h and evening 14:00 to 24:00 h). Women, compared to men, had a steeper relation of QT to RR interval indicating that when heart rate slows at night, the QT interval is more prolonged which is consistent with a greater susceptibility to fatal arrhythmias. The variability of the QT interval (the SD) was significantly (P<0.01) greater in men than women at night and in the evening but not during the day. There were differences in the ability of different QT heart rate adjustment formulae to blunt the effect of heart rate changes on the QT interval during the day. CONCLUSION: The time of the day that the QT interval is assessed should be considered. The QT heart rate relationship is different in women than in men especially at night. QT interval variability is greater at night especially in men. There are differences in the ability of QT heart rate adjustment formulae to blunt the effect of heart rate on the QT interval. Differences in the QTc at night might be the basis for the higher prevalence of sudden death in women at night.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".